Senior Data Scientist - Recommendations - FARFETCH

PT Lisbon
08 Dec 2021
04 Feb 2022
Full Time
FARFETCH exists for the love of fashion. Our mission is to be the global platform for luxury fashion, connecting creators, curators, and consumers.

We're a positive platform for good, bringing together an incredible creative community made up of our people, our partners, and our customers. This community is at the heart of our business success. We welcome differences, empower individuality and celebrate diverse skills and perspectives, creating an inclusive environment for everyone. We are FARFETCH for All.


We're a Data team that does it all: big data engineering, machine learning, and deep-dive analytics and insight. We're a diverse, global team that creates Data solutions to provide an unrivaled customer experience. Whether it's churning gigabytes of e-commerce data, using AI to recommend the latest trends, or understanding our customers better than anyone else, we use data to promote FARFETCH's growth.


Our Lisbon office is located in Portugal's cosmopolitan capital. Mostly the teams here are focused on Technology and Store of the Future. In this office, Farfetchers like to have catch-ups in the ball pit or creative moments by the grand piano!


Farfetch is building the next-generation intelligent platform for online luxury fashion, powered by large-scale data and state-of-the-art Machine Learning, Deep Learning, and Computer Vision algorithms. You will join an experienced team of Data Scientists, Engineers, and Product designers to help build, through research and experimentation, our data-driven products.


    • Design state of the art algorithms in the area of Recommender systems;
    • Conduct practical research with a scientific mindset, and a focus on delivery;
    • Work with the engineering team to integrate ML algorithms into the platform;
    • Engage with partners, product managers and designers to help bring a shared vision of a luxury fashion recommender system;
    • You will be able and encouraged to contribute to scientific and technical publications. We often contribute to top tier conferences (RecSys, KDD, ECML-PKDD, ECIR, ...).


    • MSc or PhD in a quantitative discipline: Machine Learning, Computer Science, Statistics, Applied Mathematics, Physics or related fields.
    • Minimum of 3 years experience in a Data Science related role working within an e-commerce environment.
    • Experience in Recommender Systems. Practical contact with large-scale recommender systems in production.
    • Experienced in online testing methodologies (AB Testing, Multi-armed bandits). Experienced in designing and analyzing online experiments is valued.
    • Fluent in Python and common numerical and ML packages (NumPy, SciPy, Scikit-Learn, Pandas, Keras, TensorFlow, PyTorch, and PySpark). Experience developing production software.
    • Experienced dealing with large amounts of data and knowledge of big data technologies (Spark, Data Bricks).
    • Able to communicate findings and data science concepts.
    • Fluent in English, both written and spoken.
    • Interested in keeping up-to-date with scientific advancements.


    • Health insurance for the whole family, flexible working environment and well-being support and tools
    • Extra days off, sabbatical program and days for you to give back for the community
    • Training opportunities and free access to Udemy
    • Flexible benefits program
    • FARFETCH Equity plan


    • FARFETCH is an equal opportunities employer ensuring that all applicants are treated equally and fairly throughout our recruitment process. We are determined that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, or any other basis prohibited by applicable law. We continue to build our consciously inclusive culture as part of our Positively FARFETCH strategy throughout our business, partnerships and communities.

Your main goal is to promote the use of personalization for every service across the Farfetch platform, as an example you will help develop personalized recommendations, rankings and search results.${description2}